Zobrazeno 1 - 10
of 2 621
pro vyhledávání: '"Network Inference"'
Autor:
Konrad Grützmann, Theresa Kraft, Matthias Meinhardt, Friedegund Meier, Dana Westphal, Michael Seifert
Publikováno v:
Computational and Structural Biotechnology Journal, Vol 23, Iss , Pp 1036-1050 (2024)
Melanoma, the deadliest form of skin cancer, can metastasize to different organs. Molecular differences between brain and extracranial melanoma metastases are poorly understood. Here, promoter methylation and gene expression of 11 heterogeneous patie
Externí odkaz:
https://doaj.org/article/22878d96341a4e81866b8b51ae880f20
Publikováno v:
BMC Bioinformatics, Vol 25, Iss S2, Pp 1-20 (2024)
Abstract Background With the advance in single-cell RNA sequencing (scRNA-seq) technology, deriving inherent biological system information from expression profiles at a single-cell resolution has become possible. It has been known that network modeli
Externí odkaz:
https://doaj.org/article/f8c8af8d92f34b618ab172c9c7508f61
Autor:
Matteo Bouvier, Souad Zreika, Elodie Vallin, Camille Fourneaux, Sandrine Gonin-Giraud, Arnaud Bonnaffoux, Olivier Gandrillon
Publikováno v:
BMC Bioinformatics, Vol 25, Iss 1, Pp 1-21 (2024)
Abstract Background Inference of Gene Regulatory Networks (GRNs) is a difficult and long-standing question in Systems Biology. Numerous approaches have been proposed with the latest methods exploring the richness of single-cell data. One of the curre
Externí odkaz:
https://doaj.org/article/9ad868f8016b4126a03bbf60f673194c
Autor:
Hajra Ashraf, Plamena Dikarlo, Aurora Masia, Ignazio R. Zarbo, Paolo Solla, Umer Zeeshan Ijaz, Leonardo A. Sechi
Publikováno v:
Gut Pathogens, Vol 16, Iss 1, Pp 1-12 (2024)
Abstract Background In gut ecosystems, there is a complex interplay of biotic and abiotic interactions that decide the overall fitness of an individual. Divulging the microbe-microbe and microbe-host interactions may lead to better strategies in dise
Externí odkaz:
https://doaj.org/article/6a1feaa8b1bc493f8d4f1ebc5d6a9544
Publikováno v:
Advanced Science, Vol 11, Iss 46, Pp n/a-n/a (2024)
Abstract Quantifying molecular regulations between genes/molecules causally from observed data is crucial for elucidating the molecular mechanisms underlying biological processes at the network level. Presently, most methods for inferring gene regula
Externí odkaz:
https://doaj.org/article/fa894eca3c404335abd246cd72892dca
Publikováno v:
Foundations of Computing and Decision Sciences, Vol 49, Iss 2, Pp 121-138 (2024)
To address the issue of insufficient accuracy in consumer recommendation systems, a new biased network inference algorithm is proposed based on traditional network inference algorithms. This new network inference algorithm can significantly improve t
Externí odkaz:
https://doaj.org/article/9ac73c5e4aea41ec967dcc768cf9ee23
Publikováno v:
Applied Network Science, Vol 9, Iss 1, Pp 1-22 (2024)
Abstract Reconstructing dynamics of complex systems from sparse, incomplete time series data is a challenging problem with applications in various domains. Here, we develop an iterative heuristic method to infer the underlying network structure and p
Externí odkaz:
https://doaj.org/article/27a0c679926346d89ec931cd01fc4c4b
Publikováno v:
Genome Biology, Vol 25, Iss 1, Pp 1-27 (2024)
Abstract Inferring gene regulatory networks (GRNs) from single-cell data is challenging due to heuristic limitations. Existing methods also lack estimates of uncertainty. Here we present Probabilistic Matrix Factorization for Gene Regulatory Network
Externí odkaz:
https://doaj.org/article/4c075ca7a334478292f5f3fabd956d5f
Publikováno v:
IEEE Access, Vol 12, Pp 159952-159965 (2024)
Collaborative Deep Neural Network Inference (CDNN) has emerged as one of the significant strategies for efficient and lightweight computation on resource-constrained devices (like drones), especially in the case of adverse events like natural disaste
Externí odkaz:
https://doaj.org/article/3a7b49454cc64688a78fc297d37e3fb4